Course Details

Camera Types: RGB, IR, Depth Cameras, Stereo Vision, Industrial Cameras

Assessment – Camera Types: RGB, IR, Depth Cameras, Stereo Vision, Industrial Cameras

Lens Selection, Lighting Conditions, Shutter Speed, Frame Rate

Assessment – Lens Selection, Lighting Conditions, Shutter Speed, Frame Rate

Using USB And CSI Cameras with Raspberry Pi or Jetson

Assessment – Using USB And CSI Cameras with Raspberry Pi or Jetson

Camera Calibration and Distortion Correction

Assessment – Camera Calibration and Distortion Correction

Thresholding, Adaptive Thresholding

Assessment – Thresholding, Adaptive Thresholding

ROI Extraction, Resizing, Normalization, Augmentation

Assessment – ROI Extraction, Resizing, Normalization, Augmentation

Feature Extraction: HOG, SIFT, ORB

Assessment – Feature Extraction: HOG, SIFT, ORB

Geometric Transformations: Perspective Correction, Affine Warp

Assessment – Geometric Transformations: Perspective Correction, Affine Warp

Background Subtraction, Motion Detection

Assessment – Background Subtraction, Motion Detection

Object Tracking: Centroid Tracking, Kalman Filters

Assessment – Object Tracking: Centroid Tracking, Kalman Filters

Template Matching, Correlation Filters

Assessment – Template Matching, Correlation Filters

Color Histogram Tracking

Assessment – Color Histogram Tracking

ML Workflows with Scikit-Learn

Assessment – ML Workflows with Scikit-Learn

Features vs Labels, Training/Testing Datasets

Assessment – Features vs Labels, Training/Testing Datasets

SVM, KNN, Decision Trees for Classification

Assessment – SVM, KNN, Decision Trees for Classification

Image Classification Using Classical Pipelines

Assessment – Image Classification Using Classical Pipelines

Intro to Orange Data Mining for Image Workflows

Assessment – Intro to Orange Data Mining for Image Workflows

Drag-And-Drop Pipelines for Feature Selection, Classification and Visualization

Assessment – Drag-And-Drop Pipelines for Feature Selection, Classification and Visualization

Custom Widgets for Image Inputs and Preprocessing

Assessment – Custom Widgets for Image Inputs and Preprocessing

Integration with Scikit-Learn Models

Assessment – Integration with Scikit-Learn Models

Artificial Neural Networks Recap

Forward and Backward Propagation

Introduction to TensorFlow/Keras and PyTorch

Setting Up GPU Environments (Colab/Jetson Nano)

CNN Architecture and Layers

Pooling, Activation, Dropout, Batch Normalization

Image Classification Using CNNs (MNIST, CIFAR-10)

Transfer Learning (VGG, Resnet, MobileNet)

YOLO (You Only Look Once): YOLOv5, YOLO-NAS

SSD, Faster-RCNN: Pros And Cons

Real-Time Detection using Webcam/Video Stream

Annotating Custom Datasets (RoboFlow, CVAT)

Visual Inspection: Surface Defects, PCB Inspection, Misalignment

OCR And Barcode/QR Detection

Pose Estimation and Measurement

Object Counting and Sorting

Stereo Vision, Depth Sensors (RealSense, ZED)

Point Cloud Basics and 3D Reconstruction

SLAM Basics for Spatial Mapping

Open3D And PCL Usage

Semantic vs Instance Segmentation

UNet and Mask-RCNN Architectures

Dataset Preparation and Annotation for Segmentation

Applications: Robotic Grasping, Crop Segmentation

Jetson Nano/Xavier, Coral TPU, OpenVINO Devices

Power, Cooling, Camera Interfaces, Deployment Options

Accelerating Inference with TensorRT, ONNX, TFLite

Building Docker Containers for Models

Flask/FastAPI REST APIs for Camera Input

Integrating Camera + AI Models with Node-RED

Offline vs Connected Deployment Considerations

Frame Skipping, Threading for Performance

Handling Low-Latency Inference Pipelines

Stream Processing and MQTT Integration

Alerting On Anomaly or Defect Detection